Businesses typically generate vast amounts of data through their day-to-day activities. Such business data can be analyzed to discover meaningful insights about a business, for example. However, accessing and analyzing such business data can be challenging and time-consuming. For example, a business may utilize data that is stored in different types of databases (e.g., relational or SQL-based databases versus NoSQL-based databases). In another example, the business may also utilize data that is stored in various files (e.g., records, logs, documents, etc.) and/or media objects (e.g., audio, video, etc.). These files may each utilize a different file format and/or structure, thereby creating incompatibilities among the different types of data. Further, since different teams may be restricted to certain data, in some instances, such data may be segregated in different silos, which can create difficulties in combining and analyzing data.